Systems and methods for recognizing symbols in images

ABSTRACT

A computer-implemented method comprises generating a description of a character symbol from a binarized image; comparing a template for the character symbol with the description of the character symbol based on a reference description, wherein the template comprises a grid of cells, a set of local features which may be present in the grid of cells, the reference description specifying which member of the set of local features should be present or absent in the grid of cells, and a threshold of an accepted deviation with the description of the character symbol; assigning a penalty value to the description of the character symbol via a cost function when a discrepancy exists based on the comparing; selecting the template as a match candidate for the character symbol when the penalty value is below the threshold; recognizing the character symbol based on the selecting.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/094,472, filed on Apr. 8, 2016, which is herein fully incorporated byreference for all purposes.

TECHNICAL FIELD

Generally, the present disclosure relates image processing.

BACKGROUND

In the present disclosure, where a document, an act and/or an item ofknowledge is referred to and/or discussed, then such reference and/ordiscussion is not an admission that the document, the act and/or theitem of knowledge and/or any combination thereof was at the prioritydate, publicly available, known to the public, part of common generalknowledge and/or otherwise constitutes prior art under the applicablestatutory provisions; and/or is known to be relevant to an attempt tosolve any problem with which the present disclosure is concerned with.Further, nothing is disclaimed.

An image is captured via an image capture device, such as a camera.Often, the image contains information, such as an alphanumerical string,which is desired to be extracted for processing, such as license platerecognition. Typically, such information is extracted via an opticalcharacter recognition (OCR) process, which involves a pre-processingphase, a character recognition phase, and a post-processing phase.Although the character recognition phase is fairly developed, thecharacter recognition phase is still not sufficiently precise incharacter recognition. Therefore, there is a desire to improve thecharacter recognition phase.

SUMMARY

The present disclosure at least partially addresses at least one of theabove. However, the present disclosure can prove useful to othertechnical areas. Therefore, the claims should not be construed asnecessarily limited to addressing any of the above.

In an embodiment, a method of character recognition comprises:generating, by a computer, a description of a character symbol from abinarized image; comparing, by the computer, a template for thecharacter symbol with the description of the character symbol based on areference description, wherein the template comprises a grid of cells, aset of local features which may be present in the grid of cells, thereference description specifying which member of the set of localfeatures should be present or absent in the grid of cells, and athreshold of an accepted deviation with the description of the charactersymbol; assigning, by the computer, a penalty value to the descriptionof the character symbol via a cost function when a discrepancy existsbased on the comparing; selecting, by the computer, the template as amatch candidate for the character symbol when the penalty value is belowthe threshold; recognizing, by the computer, the character symbol basedon the selecting.

In an embodiment, a device comprises a computer configured to: generatea description of a character symbol from a binarized image; compare atemplate for the character symbol with the description of the charactersymbol based on a reference description, wherein the template comprisesa grid of cells, a set of local features which may be present in thegrid of cells, the reference description specifying which member of theset of local features should be present or absent in the grid of cells,and a threshold of an accepted deviation with the description of thecharacter symbol; assign a penalty value to the description of thecharacter symbol via a cost function when a discrepancy exists based onthe comparing; select the template as a match candidate for thecharacter symbol when the penalty value is below the threshold;recognize the character symbol based on the selecting.

Additional features and advantages of various embodiments are set forthin the description which follows, and in part is apparent from thedescription. Various objectives and other advantages of the presentdisclosure are realized and attained by various structures particularlypointed out in the exemplary embodiments in the written description andclaims hereof as well as the appended drawings. It is to be understoodthat both the foregoing general description and the following detaileddescription are exemplary and explanatory and are intended to providefurther explanation of the present disclosure as claimed.

BRIEF DESCRIPTION OF DRAWINGS

The accompanying drawings constitute a part of this specification andillustrate an embodiment of the present disclosure and together with thespecification, explain the present disclosure.

FIG. 1 shows a schematic view of an embodiment of a network topologyaccording to the present disclosure.

FIG. 2 shows a schematic view of a bounding box broken into a grid ofcells according to the present disclosure.

FIG. 3 shows a flowchart of an embodiment of a process for recognizing asymbol in an image according to the present disclosure.

FIG. 4 shows a flowchart of an embodiment of a process for generating atemplate according to the present disclosure.

FIG. 5 shows a flowchart of an embodiment of a process for generating adescription of a symbol according to the present disclosure.

FIG. 6 shows a flowchart of an embodiment of a process for selecting atemplate corresponding to a symbol according to the present disclosure.

DETAILED DESCRIPTION

The present disclosure is now described more fully with reference to theaccompanying drawings, in which example embodiments of the presentdisclosure are shown. The present disclosure may, however, be embodiedin many different forms and should not be construed as necessarily beinglimited to the example embodiments disclosed herein. Rather, theseexample embodiments are provided so that the present disclosure isthorough and complete, and fully conveys the concepts of the presentdisclosure to those skilled in the relevant art.

FIG. 1 shows a schematic view of an embodiment of a network topologyaccording to the present disclosure. A network topology 100 comprises anetwork 102, a first client 104, a second client 106, a third client108, a server 110, a data storage controller 112, a data storage 114,and a camera 116. All components of the topology 100 can be coupleddirectly or indirectly, whether in a wired or a wireless manner. Notethat each of components of the topology 100 can be implemented in logic,whether hardware-based or software-based. For example, when the logic ishardware-based, then such logic can comprise circuitry, such asprocessors, memory, input devices, output devices, or other hardware,that is configured, such as via programming or design, to implement afunctionality of a respective component. Likewise, when the logic issoftware-based, then such logic can comprise one or more instructions,such as assembly code, machine code, object code, source code, or anyother type of instructions, which when executed, such as via running orcompilation, implement a functionality of a respective component.Further, note that at least one of such components can be implemented asa service. Moreover, note that at least two of such components can behosted on one computing system/hardware/device or each be distinctlyhosted.

The topology 100 is based on a distributed network operation model whichallocates tasks/workloads between servers, which provide aresource/service, and clients, which request the resource/service. Theservers and the clients illustrate different computers/applications, butin some embodiments, the servers and the clients reside in or are onesystem/application. Further, in some embodiments, the topology 100entails allocating a large number of resources to a small number ofcomputers, such as the server 110, where complexity of the clients, suchas the clients 104, 106, 108, depends on how much computation isoffloaded to the small number of computers, i.e., more computationoffloaded from the clients onto the servers leads to lighter clients,such as being more reliant on network sources and less reliant on localcomputing resources. Note that other computing models are possible aswell. For example, such models can comprise decentralized computing,such as peer-to-peer (P2P), for instance Bit-Torrent®, or distributedcomputing, such as via a computer cluster where a set of networkedcomputers works together such that the computer can be viewed as asingle system.

The network 102 includes a plurality of nodes, such as a collection ofcomputers and/or other hardware interconnected via a plurality ofcommunication channels, which allow for sharing of resources and/orinformation. Such interconnection can be direct and/or indirect. Thenetwork 102 can be wired and/or wireless. The network 102 can allow forcommunication over short and/or long distances, whether encrypted and/orunencrypted. The network 102 can operate via at least one networkprotocol, such as Ethernet, a Transmission Control Protocol(TCP)/Internet Protocol (IP), and so forth. The network 102 can have anyscale, such as a personal area network (PAN), a local area network(LAN), a home area network, a storage area network (SAN), a campus areanetwork, a backbone network, a metropolitan area network, a wide areanetwork (WAN), an enterprise private network, a virtual private network(VPN), a virtual network, a satellite network, a computer cloud network,an internetwork, a cellular network, and so forth. The network 102 canbe and/or include an intranet and/or an extranet. The network 102 can beand/or include Internet. The network 102 can include other networksand/or allow for communication with other networks, whether sub-networksand/or distinct networks, whether identical and/or different from thenetwork 102 in structure or operation. The network 102 can includehardware, such as a computer, a network interface card, a repeater, ahub, a bridge, a switch, an extender, an antenna, and/or a firewall,whether hardware based and/or software based. The network 102 can beoperated, directly and/or indirectly, by and/or on behalf of one and/ormore entities or actors, irrespective of any relation to contents of thepresent disclosure.

The server 110 can be hardware-based and/or software-based. The server110 is and/or is hosted on, whether directly and/or indirectly, a servercomputer, whether stationary or mobile, such as a kiosk, a workstation,a vehicle, whether land, marine, or aerial, a desktop, a laptop, atablet, a mobile phone, a mainframe, a supercomputer, a server farm, andso forth. The server computer can comprise another computer systemand/or a cloud computing network. The server computer can run any typeof operating system (OS), such as MacOS®, Windows®, Android®, Unix®,Linux® and/or others. The server computer can include and/or be coupledto, whether directly and/or indirectly, an input device, such as amouse, a keyboard, a camera, whether forward-facing and/or back-facing,an accelerometer, a touchscreen, a biometric reader, a clicker, amicrophone, or any other suitable input device. The server computer caninclude and/or be coupled to, whether directly and/or indirectly, anoutput device, such as a display, a speaker, a headphone, a vibrator, aprinter, or any other suitable output device. In some embodiments, theinput device and the output device can be embodied in one unit, such asa touch-enabled display, which can be haptic. The server computer caninclude circuitry, such as a receiver chip, for geolocation/globalpositioning determination, such as via a global positioning system(GPS), a signal triangulation system, and so forth. The server computercan be equipped with near-field-communication (NFC) circuitry, such asan NFC chip. The server computer can host, run, and/or be coupled to,whether directly and/or indirectly, a database, such as a relationaldatabase or a non-relational database, such as a post-relationaldatabase, an in-memory database, or others, which can feed, avail, orotherwise provide data to at least one of the server 110, whetherdirectly and/or indirectly. The server 110 can be at least one of anetwork server, an application server, or a database server.

The server 110, via the server computer, can be in communication withthe network 102, such as directly and/or indirectly, selectively and/orunselectively, encrypted and/or unencrypted, wired and/or wireless. Suchcommunication can be via a software application, a software module, amobile app, a browser, a browser extension, an OS, and/or anycombination thereof. For example, such communication can be via a commonframework/application programming interface (API), such as HypertextTransfer Protocol Secure (HTTPS).

At least one of the clients 104, 106, 108 can be hardware-based and/orsoftware-based. At least one of the clients 104, 106, 108 is and/or ishosted on, whether directly and/or indirectly, a client computer,whether stationary or mobile, such as a terminal, a kiosk, aworkstation, a vehicle, whether land, marine, or aerial, a desktop, alaptop, a tablet, a mobile phone, a mainframe, a supercomputer, a serverfarm, and so forth. The client computer can comprise another computersystem and/or cloud computing network. The client computer can run anytype of OS, such as MacOS®, Windows®, Android®, Unix®, Linux® and/orothers. The client computer can include and/or be coupled to an inputdevice, such as a mouse, a keyboard, a camera, whether forward-facingand/or back-facing, an accelerometer, a touchscreen, a biometric reader,a clicker, a microphone, or any other suitable input device. The clientcomputer can include and/or be coupled to an output device, such as adisplay, a speaker, a headphone, a joystick, a vibrator, a printer, orany other suitable output device. In some embodiments, the input deviceand the output device can be embodied in one unit, such as atouch-enabled display, which can be haptic. The client computer caninclude circuitry, such as a receiver chip, for geolocation/globalpositioning determination, such as via a GPS, a signal triangulationsystem, and so forth. The client computer can be equipped with NFCcircuitry, such as an NFC chip. The client computer can host, run and/orbe coupled to, whether directly and/or indirectly, a database, such as arelational database or a non-relational database, such as apost-relational database, an in-memory database, or others, which canfeed or otherwise provide data to at least one of the clients 104, 106,108, whether directly and/or indirectly.

At least one of the clients 104, 106, 108, via the client computer, isin communication with network 102, such as directly and/or indirectly,selectively and/or unselectively, encrypted and/or unencrypted, wiredand/or wireless, via contact and/or contactless. Such communication canbe via a software application, a software module, a mobile app, abrowser, a browser extension, an OS, and/or any combination thereof. Forexample, such communication can be via a common framework/API, such asHTTPS. In some embodiments, the server 110 and at least one of theclients 104, 106, 108 can also directly communicate with each other,such as when hosted in one system or when in local proximity to eachother, such as via a short range wireless communication protocol, suchas infrared or Bluetooth®. Such direct communication can be selectiveand/or unselective, encrypted and/or unencrypted, wired and/or wireless,via contact and/or contactless. Since many of the clients 104, 106, 108can initiate sessions with the server 110 relatively simultaneously, insome embodiments, the server 110 employs load-balancing technologiesand/or failover technologies for operational efficiency, continuity,and/or redundancy.

The storage controller 112 can comprise a device which manages a diskdrive or other storage, such as flash storage, and presents the diskdrive as a logical unit for subsequent access, such as various datainput/output (IO) operations, including reading, writing, editing,deleting, updating, searching, selecting, merging, sorting, or others.The storage controller 112 can include a front-end side interface tointerface with a host adapter of a server and a back-end side interfaceto interface with a controlled disk storage. The front-end sideinterface and the back-end side interface can use a common protocol ordifferent protocols. Also, the storage controller 112 can comprise anenterprise controller, which can comprise a physically independentenclosure, such as a disk array of a storage area network or anetwork-attached storage server. For example, the storage controller 112can comprise a redundant array of independent disks (RAID) controller.In some embodiments, the storage controller 112 can be lacking such thata storage can be directly accessed by the server 110. In someembodiments, the controller 222 can be unitary with the server 110.

The storage 114 can comprise a storage medium, such as at least one of adata structure, a data repository, a data mart, or a data store. Forexample, the storage medium comprises a database, such as a relationaldatabase, a non-relational database, an in-memory database, or others,which can store data and allow access to such data to the storagecontroller 112, whether directly and/or indirectly, whether in a rawstate, a formatted state, an organized stated, or any other accessiblestate. For example, the data can comprise image data, sound data,alphanumeric data, or any other data. For example, the storage 114 cancomprise a database server. The storage 114 can comprise any type ofstorage, such as primary storage, secondary storage, tertiary storage,off-line storage, volatile storage, non-volatile storage, semiconductorstorage, magnetic storage, optical storage, flash storage, hard diskdrive storage, floppy disk drive, magnetic tape, or other data storagemedium. The storage 114 is configured for various data I/O operations,including reading, writing, editing, modifying, deleting, updating,searching, selecting, merging, sorting, encrypting, de-duplicating, orothers. In some embodiments, the storage 114 can be unitary with thestorage controller 112. In some embodiments, the storage 114 can beunitary with the server 110.

The camera 116 comprises an optical instrument for capturing andrecording images, which may be stored locally, transmitted to anotherlocation, or both. The images may be individual still photographs orsequences of images constituting videos. The images can be analog ordigital. The camera 116 can comprise any type of lens, such as convex,concave, fisheye, or others. The camera 116 can comprise any focallength, such as wide angle or standard. The camera 116 can comprise aflash illumination output device. The camera 116 can comprise aninfrared illumination output device. The camera 116 can is powered viamains electricity, such as via a power cable or a data cable. In someembodiments, the camera 116 is powered via at least one of an onboardrechargeable battery, such as a lithium-ion battery, or an onboardrenewable energy source, such as a photovoltaic cell, a wind turbine, ora hydropower turbine. The camera 116 is coupled to the first client 104,whether directly or indirectly, whether in a wired or wireless manner.For example, the client 104 can power the camera 116. The camera 116 canbe configured for geotagging, such as via modifying an image file withgeolocation/coordinates data. The camera 116 can be front or rearfacing, if the client 104 is a mobile device, such as a smartphone, atablet, or a laptop. The camera 116 can include or be coupled to amicrophone. The camera 116 can be a pan-tilt-zoom camera.

In one mode of operation, the camera 116 sends a captured image to theclient 104, which then sends the image to the server 110 over thenetwork 102. The server 110 stores the image in the storage 114 via thestorage controller 112. The second client 106 can comprise a managerterminal in signal communication with the server 110 over the network102 to manage the server 110 over the network 102. The third client 108can comprise a customer terminal in signal communication with the server110 to access the image over the network 102, as captured via the camera116 and stored in the storage 114 via the storage controller 112. Themanager terminal can comprise a plurality of input/output devices, suchas a keyboard, a mouse, a speaker, a display, a printer, a camera, orothers, with the manager terminal being embodied as a tablet computer, alaptop computer, or a workstation computer, where the display can outputa graphical user interface (GUI) configured to input or to outputinformation, whether alphanumerical, symbolical, or graphical, to amanager operating the manager terminal. The input can include variousmanagement information for managing the server 110 and the output caninclude a status of the server 110, the storage controller 112, or thestorage 114. The manager terminal can be configured to communicate withother components of the topology 100 over the network 102 for managementor maintenance purposes, such as to program, update, modify, or adjustany server, controller, computer, or storage in the topology 100. TheGUI can also be configured to present other management or non-managementinformation as well. The manager terminal can be configured to printreports, such as in color or grayscale.

Note that any computing device as described herein comprises at least aprocessing unit and a memory unit operably coupled to the processingunit. The processing unit comprises a hardware processor, such as asingle core or a multicore processor. For example, the processing unit102 comprises a central processing unit (CPU), which can comprise aplurality of cores for parallel/concurrent independent processing. Thememory unit comprises a computer-readable storage medium, which can benon-transitory. The storage medium stores a plurality ofcomputer-readable instructions for execution via the processing unit.The instructions instruct the processing unit to facilitate performanceof a method for recognizing a symbol in an image, as disclosed herein.For example, the processing unit and the memory unit can enable variousfile or data input/output operations, including reading, writing,editing, modifying, deleting, updating, searching, selecting, merging,sorting, encrypting, de-duplicating, or others. The memory unit cancomprise at least one of a volatile memory unit, such as random accessmemory (RAM) unit, or a non-volatile memory unit, such as anelectrically addressed memory unit or a mechanically addressed memoryunit. For example, the electrically addressed memory comprises a flashmemory unit. For example, the mechanically addressed memory unitcomprises a hard disk drive. The memory unit can comprise a storagemedium, such as at least one of a data repository, a data mart, or adata store. For example, the storage medium can comprise a database,such as a relational database, a non-relational database, an in-memorydatabase, or other suitable databases, which can store data and allowaccess to such data via a storage controller, whether directly and/orindirectly, whether in a raw state, a formatted state, an organizedstated, or any other accessible state. The memory unit can comprise anytype of storage, such as a primary storage, a secondary storage, atertiary storage, an off-line storage, a volatile storage, anon-volatile storage, a semiconductor storage, a magnetic storage, anoptical storage, a flash storage, a hard disk drive storage, a floppydisk drive, a magnetic tape, or other suitable data storage medium.

FIG. 2 shows a schematic view of a bounding box broken into a grid ofcells according to the present disclosure. A bounding box 200 issegmented into a predetermined number of cells 202, along a verticalplane and a horizontal plane. Each of the cells 202 is indicated bysolid lines. Each of the cells 202 contains a plurality of pixels 204.The pixels 204 are indicated by broken lines. As shown in FIG. 2, thebounding box 200 comprises four cells 202 extending consecutively alonga horizontal axis and six cells 202 extending consecutively along avertical axis, with each of the cells 202 containing four pixels 204 inan unshared manner. Note that a number of pixels 204 per cell 202 canvary. For example, the number of pixels 204 can depend on how thebounding box 200 is divided into the cells 204. Further, note thatalthough letter D is shown in the bounding box 200, any symbol, such asalphanumeric, of any alphabet/library can be used, such as O, Q, A, E,I, G, S, 2, 4, 7, 3, 8, 0, or others.

Note that the bounding box 200 can be shaped in any closed shape, suchas a rectangle, a square, a triangle, or any other closed shape. Forexample, the bounding box 200 can comprise more cells 202 along thevertical axis than the horizontal axis, such as via a verticallyrectangular shape. The cells 202 can be shaped in any closed shape, suchas a rectangle, a square, a triangle, or any other closed shape. Forexample, the cells 202 can enable tiling (or paving) an entire area ofthe bounding box 200 in a rectangular or a square fashion. The cells 202can be identical to or different from each other in shape or size. Thecells 202 can total to an even or an odd amount. A ratio of a number ofcells 202 by height (the vertical axis) and width (the horizontal axis)substantially corresponds to a typical ratio of a recognizable font,which in FIG. 2 is Arial.

Although each of the cells 202 contains four pixels 204, any amount ofpixels 204 can be contained in a single cell 202, such as 2×2 pixels,4×6 pixels, 6×5 pixels, or others. In some embodiments, at least twocells 202 differ in amount of pixels 204 therein, such as one cell 202having 6 pixels and another cell 202 having 8 pixels.

FIG. 3 shows a flowchart of an embodiment of a process for recognizing asymbol in an image according to the present disclosure. A process 300includes a plurality of blocks 302-314. The process 300 is performed viaa computer architecture of FIG. 1. In some embodiments, the process 300is distributed over a plurality of computers. The process 300 enables arecognition of a symbol via a binary image thereof. For example, animage is camera-captured or machine-generated. The image comprises thesymbol. The image can be monochrome, grayscale, or color. The image canbe a still-photo or a portion of a video, such as a single frame. Theimage is pre-processed, such as de-skewed, de-speckled, binarized,segmented, normalized, or pre-processed in any other way. Uponbinarization of the image, such as via a grayscale threshold applicationprocess or otherwise, a binary image is generated, where the binaryimage comprises a digital image, which comprises a plurality of pixels,where each of the pixels comprises two possible values. For example, thebinary image can be a black and white image, where 1 represents blackand 0 represents white. However, note that any two colors can be used,such as red represented by 1 and green represented by 0. A color usedfor the symbol in the binary image is a foreground color, such as black,while a non-colored area is a background color, such as white.

The symbol is representative of a glyph, such as a printed block type ora non-cursive character, in any font, such as Arial, or size, such as 12as used in Microsoft Word®. For example, the symbol can be alphanumericand comprise a letter Z or x, such as contained in a license plate or adocument page. However, note that the symbol representative of the glyphcan be a portion of any type of writing system/alphabet in any font inany size, such as Latin, Cyrillic, Hebrew, Indic, Bengali (Bangla),Devanagari, Tamil characters of any font or size. For example, thewriting system/alphabet of a language can be used, where the writingsystem/alphabet includes characters which are roughly of similarvertical size. Further, although the process 300 is scale invariant, insome embodiments, the process 300 can be scale variant.

In a block 302, a template for a symbol is generated. The templatecomprises an appearance variant of the symbol. Such generation can occurfor a plurality of symbols as well. For example, a set of templates fora set of symbols can be generated. Note that more than one template canbe generated per symbol, such as for a letter Z there can be more thanone template, such as one for each font. For example, one or moretemplates can be generated in a stage preceding an actual recognitionstage.

Such template generation can occur via segmenting a bounding box into apredetermined number of cells, along a vertical plane and a horizontalplane. For example, the bounding box can contain a grid of cells. Thebounding box is sized to contain the appearance variant therein. Thebounding box can be shaped in any closed shape, such as a rectangle, asquare, a triangle, or any other closed shape. For example, the boundingbox can comprise more cells along the vertical axis than the horizontalaxis, such as via a rectangular shape. The cells can be shaped in anyclosed shape, such as a rectangle, a square, a triangle, or any otherclosed shape. The cells can be identical to or different from each otherin shape. The cells can total to an even or an odd amount. A ratio of anumber of cells by height (the vertical axis) and width (the horizontalaxis) substantially corresponds to a typical ratio of a recognizablefont symbol. Each of the cells contains a plurality of pixels, where thepixels are not shared with other cells. For example, at least one of thecells can contain 2×2 pixels, 4×6 pixels, 6×5 pixels, or others.

Upon segmenting the bounding box into the cells, one or more localfeatures are specified, where such local features may be present in atleast one of the cells. For example, the local features can comprisehorizontal/vertical/diagonal lines, edges, corners, blobs, strokeaspects, boundaries, contour directions, concavities/convexities, or anyother local image characteristics which enable location of local imagestructures in a repeatable manner. For example, one or more localfeatures are specified in a set. For example, one or more local featurescan be specified via a reference, a pointer, or an identifier, such asan alphanumeric symbol, a symbol string, a memory location, or others.

Upon specifying the local features, for each appearance variant ofwriting/typing/depicting the symbol, a reference description isgenerated, where for each local feature specified in the set of one ormore local features, one or more of the cells is specified which shouldcontain or not contain that respective local feature. For example, suchfunctionality can be performed via marking of important pixels for eachlocal feature.

The reference description comprises two sets of tables, such as matricesbased on a number of local features selected for analysis. For example,a plurality of matrices can be generated based on a number of selectedlocal features for analysis. The first set is a mask set and the secondset is a pattern set. Each of the first set and the second set comprisesa same number of cells as segmented in the bounding box. In each of thefirst set and the second set, each local feature is represented via itsown table. Therefore, the first set and the second set are related on atleast a cell basis.

In the mask set, each table indicates or specifies cells in whichpresence or absence of a respective local feature appears meaningful forrecognition (important for location matching—which cells should be andshould not be considered during a candidate comparison). This appearanceis indicated by a value, such as a binary value, for instance 1.However, remaining table cells are populated with a 0 value, if binarysystem is used. Correspondingly, for that same local feature, thepattern set indicates whether or not a given local feature should bepresent in a given cell of a symbol being analyzed (important forfeature presence). Therefore, a value of a table in a cell can beimmaterial for symbol recognition unless a value of the correspondingmask table is one (1).

For each generated reference description, a threshold is set orassigned, where the threshold corresponds to a degree of an acceptabledeviance with a generated description of a recognizable symbol. Suchthreshold can be a value defined as a maximum number of cells where thedeviation was noted. For example, if a reference description deviatesover 5% with a description of a recognizable symbol, then that referencedescription can be rejected, as not corresponding to the recognizablesymbol. The threshold is determined based on appropriate presence orabsence of selected local features in mask selected cells of thebounding box, where the threshold corresponds to a number or percentageof cells meeting or not meeting a certain criteria.

Accordingly, such information can be populated into a template or atemplate can be generated based on such information. For example, thetemplate can be stored in a file or a record, either of which can bestored in a database.

In a block 304, a description of a symbol is generated. The symbol is inan image subject to pre-processing. Such description can be generatedbased on placing a bounding box over a symbol such that the symbol iscontained in the box. The bounding box is broken up into a predeterminednumber of cells, which is equivalent to the reference description, notedabove. For each pixel of each cell, a determination of a presence or anabsence of a selected local feature is performed. Then, for each cell,based on the same rule, a determination is performed, where thedetermination determines an absence or a presence of each of these localfeatures based on the presence of such features in individual pixelsincluded in that cell. However, note that any type or kind of rules canbe used in any combinatory or permutational manner, as user preset ordynamically set. For example, if one pixel in a cell has a localfeature, then the cell can be imputed to possess this local feature. Forexample, if all pixels in a cell have a local feature, then the wholecell can be imputed to possess this local feature. However, note thatany intermediate pixel configurations can also be used, such as one halfof pixels in a cell or two thirds of pixels in a cell or three quartersof pixels in a cell or any other fractions. Likewise, a pixel patterncan also be rule-based, such as pixels being continuous in a cell orpixels being arranged in a certain shape in a cell or pixels positionedalong an edge of a cell or any others.

In a block 306, the template is compared with the description of thesymbol. Such comparison comprises comparing the reference description ofeach variant of each symbol with the description of the symbol, as notedabove. For each local feature of the reference description and for eachcell, where the description of the symbol mandates the presence or theabsence of that local feature, a check for the presence or the absenceof this feature in the description of the symbol is performed. Note thata full vector of a presence of a local feature in a cell can be used,where the full vector is generated for each analyzed local feature.Further, note that, for example, since the template can indicate amaximum allowable difference or deviance from a description of a symbol,a recognition result can be absent.

In a block 308, a cost function is applied to a result of the comparisonof the template with the description of the symbol. In case ofdiscrepancy, based on the checking noted above, a cost, such as apenalty, is incurred, where all accrued costs are totaled, such as viasumming differences for each local feature. If the accrued costs for alllocal features exceed the threshold, as set in the referencedescription, then that symbolic variant is rejected as a result ofrecognition. For example, the cost function is evaluated on acell-by-cell basis. For example, the cost function can be based on aHemming distance. For example, the Hemming distance can be used todetermine difference between the template and the description of thesymbol.

In a block 310, a set of cost function results is generated. The set ofcost function results is based on non-rejected symbolic variants, i.e.,reference descriptions.

In a block 312, a member of the set of cost function results isidentified, wherein the member is associated with a minimum cost. Notethat more than one member can be identified. Such identification occursbased on sorting the set based on cost, such as from low to high or highto low, such as via a sorting algorithm, such as an insertion sort, aselection sort, a merge sort, a heap sort, a quick sort, a bubble sort,a shell sort, a comb sort, a counting sort, a bucket sort, a radix sort,or any other sort. Upon sorting, the member associated with the minimumcost is identified. Then, as a result of a character recognition phase,one or more reference descriptions or variants with minimum costs areselected to correspond to the symbol. In some embodiments, all remainingreference descriptions or variants are provided, yet under a condition,such as limiting to a number of output symbol matches, such as 5matches, or discarding or ignoring those remaining referencedescriptions or variants that have a cost clearly greater than others.

In a block 314, the member(s) with the minimum cost are nominated forcharacter recognition, i.e., one or more reference descriptions orvariants with minimum costs are output for corresponding to the symbol.

In some embodiments, the process 300 is performed on a per symbol basisand therefore, for example, can be used to distinguish a symbol O from asymbol D or a symbol O from a symbol Q. However, note that the process300 can be configured for performance on a per word basis, for eachsymbol contained therein.

In some embodiments, the process 300 is tweaked for a specificapplication, such as for license plate or vehicle identifierrecognition, whether at lane location in real-time or on a deferredbasis. However, note that other applications are possible as well, suchas document processing or others. For example, in license platerecognition, such tweaking can comprise developing character templatesfor a particular typeface to be recognized, like the one on licenseplates of a jurisdiction at hand.

In some embodiments, a matrix matching character recognition process ora feature extraction character recognition process comprises the process300.

FIG. 4 shows a flowchart of an embodiment of a process for generating atemplate according to the present disclosure. A process 400 includes aplurality of blocks 402-410. The process 400 is performed via a computerarchitecture of FIG. 1. In some embodiments, the process 400 isdistributed over a computer architecture of FIG. 1.

In a block 402, an area is segmented into a predetermined number ofcells. Such segmentation can occur based on a template for a symbolbeing generated. The template reflects an appearance variant of thesymbol. Such generation can occur for a plurality of symbols as well.For example, a set of templates for a set of symbols can be generated.Note that more than one template can be generated per symbol, such asfor a letter W there can be more than one template, such as one for eachfont. The segmentation involves segmenting a bounding box into apredetermined number of cells, along a vertical plane and a horizontalplane. For example, the bounding box can contain a grid of cells. Forexample, the bounding box can be rectangularly tessellated. The boundingbox is sized to contain the appearance variant therein. The bounding boxcan be shaped in any closed shape, such as a rectangle, a square, atriangle, or any other closed shape. For example, the bounding box cancomprise more cells along the vertical axis than the horizontal axis,such as via a rectangular shape. The cells can be shaped in any closedshape, such as a rectangle, a square, a triangle, or any other closedshape. The cells can be identical to or different from each other inshape. The cells can total to an even or an odd amount. A ratio of anumber of cells by height (the vertical axis) and width (the horizontalaxis) substantially corresponds to a typical ratio of a recognizablefont. Each of the cells contains a plurality of pixels, where the pixelsare not shared with other cells. For example, at least one of the cellscan contain 2×2 pixels, 4×6 pixels, 6×5 pixels, or others.

In a block 404, a local feature is specified, where the local featuremay be present in at least one of the cells. Such specification occursbased upon segmenting the bounding box into the cells, where one or morelocal features are specified, where such local features may be presentin at least one of the cells. For example, a variety of local featurescan be selected prior to template generation, based on available imageanalysis machinery or based on an appearance of font glyphs. Forexample, the local features can comprise horizontal/vertical/diagonallines, edges, corners, stroke aspects, boundaries, direction,orientations, contours, concavities/convexities, or any other localimage characteristics which enable location of local image structures ina repeatable manner. For example, one or more local features arespecified in a set.

In a block 406, a reference description for each variant of a symbol isgenerated. Such generation occurs based upon specifying the localfeatures, for each appearance variant of writing/typing/depicting thesymbol, a reference description is generated, where for each localfeature specified in the set of one or more local features, one or moreof the cells is specified which should contain or not contain thatrespective local feature. For example, such functionality allows markingof important cells for each local feature.

The reference description comprises two sets of tables, such as matricesbased on a number of local features selected for analysis. For example,a plurality of matrices can be generated based on a number of selectedlocal features for analysis. The first set is a mask set and the secondset is a pattern set. Each matrix or table of the first set and thesecond set comprises a same number of cells as segmented in the boundingbox. In each of the first set and the second set, each local feature isrepresented via its own respective table. Therefore, the first set andthe second set are related on at least a cell basis.

In the mask set, each table specifies cells in which presence or absenceof a respective local feature appears meaningful for recognition (whichcells should be and should not be considered during a candidatecomparison). This appearance is indicated by a value, such as a binaryvalue, for instance 1. However, remaining table cells are populated witha 0 value, if binary system is used. Correspondingly, for that samelocal feature, the pattern set indicates whether or not a given localfeature should be present in a given cell of a symbol being analyzed(important for feature presence). Therefore, a value of a pattern tablein a cell can be immaterial for symbol recognition unless a value of thecorresponding mask table is one (1).

In a block 408, a threshold of an acceptable deviance for the referencedescription is generated. Such generation occurs for each generatedreference description, where the threshold is set or assigned, where thethreshold corresponds to a degree of an acceptable deviance with agenerated description of a recognizable symbol. Such threshold can be avalue defined as a maximum number of cells where the deviation wasnoted. For example, if a reference description deviates over 5% with adescription of a recognizable symbol, then that reference descriptioncan be rejected, as not corresponding to the recognizable symbol. Thethreshold is determined based on appropriate presence or absence ofselected local features in selected cells of the bounding box, where thethreshold corresponds to a number or percentage of cells meeting or notmeeting a certain criteria, such as defined via a deviation gaugingmethod based on counting a number of deviant cells over all features.

In a block 410, a template is stored in a storage. The template can be afile or a record, populated or generated, as noted above.

FIG. 5 shows a flowchart of an embodiment of a process for generating adescription of a symbol according to the present disclosure. A process500 includes a plurality of blocks 502-508. The process 500 is performedvia a computer architecture of FIG. 1. In some embodiments, the process500 is distributed over a computer architecture of FIG. 1.

In a block 502, an area is segmented into a predetermined number ofcells. The symbol is in an image that has been subject topre-processing. Such description can be generated based on placing abounding box over a symbol such that the symbol is contained in the box.The bounding box is broken up into a predetermined number of cells,which is equivalent to the reference description, noted above.

In a block 504, a presence or an absence of a selected local feature foreach pixel in each cell is determined. For example, for each pixel ofeach cell, a determination of a presence or an absence of a selectedlocal feature is performed. For example, such determination can comprisecalculating a cell state with respect to the local features. In someembodiments, a pixel pattern can also be rule-based, such as pixelsbeing continuous in a cell or pixels being arranged in a certain shapein a cell or pixels positioned along an edge of a cell or any others.

In a block 506, a presence or an absence of a selected local feature ina cell is determined. For example, for each cell, based on the samerule, a determination is performed, where the determination determinesan absence or a presence of each of these local features based on thepresence of such features in individual pixels included in that cell.However, note that any type or kind of rules can be used in anycombinatory or permutational manner, as user preset or dynamically set.For example, if one pixel in a cell has a local feature, then the cellcan be imputed to possess this local feature. For example, if all pixelsin a cell have a local feature, then the whole cell can be imputed topossess this local feature. However, note that any intermediate pixelconfigurations can also be used, such as one half of pixels in a cell ortwo thirds of pixels in a cell or three quarters of pixels in a cell orany other fractions. Further, note that any combinatory or permutationalcombination of such rules can be used.

In a block 508, a description of a symbol is generated. Such descriptioncan be a file or a record, populated or generated, as noted above. Insome embodiments, at least one of the blocks 502-508 can be performedfor each feature in the selected set of local features, which will yieldthe description of the character in hand.

FIG. 6 shows a flowchart of an embodiment of a process for selecting atemplate corresponding to a symbol according to the present disclosure.A process 600 includes a plurality of blocks 602-618. The process 600 isperformed via a computer architecture of FIG. 1. In some embodiments,the process 600 is distributed over a plurality of computers. Theprocess 600 is employed based on comparing the template with thedescription of the symbol, as noted above. Such comparison comprisescomparing the reference description of each variant of each symbol withthe description of the symbol, as noted above.

In a block 602, a determination is made, where the determinationdetermines a presence or an absence of a local feature in a descriptionof symbol based on a comparison with a template. For example, suchdetermination can comprise testing if the feature flag is set for thespecific cell. For example, such determination can comprise iterationover cells. For each local feature of the reference description and foreach cell, where the description of the symbol mandates the presence orthe absence of that local feature, a check for the presence or theabsence of this feature in the description of the symbol is performed.For example, a Hemming distance can be used to determine differencebetween the template and the description of the symbol. Note that a fullvector of a presence of a local feature in one or more cells can beused, where the full vector is generated for each analyzed localfeature. Further, note that, for example, since the template canindicate a maximum allowable difference or deviance from a descriptionof a symbol, a recognition result can be absent.

In a block 604, a cost is applied if no match is found, such as via anapplication of a cost function. The cost function is applied to a resultof the comparison of the template with the description of the symbol. Incase of discrepancy, based on the checking noted above, the cost isincurred.

In a block 606, a totaling of the cost with other costs, if any, isperformed. In case of discrepancy, based on the checking noted above, acost is incurred, where all accrued costs are totaled, such as viasumming differences for each local feature.

In a block 608, a determination is made, where the determinationdetermines if a threshold has been exceeded. Note that vice versaconfiguration can be used as well, where the threshold has not been met.For example, the threshold can be exceeded or not met. If the thresholdhas been exceeded, a block 610 is performed. Otherwise, a block 612 isperformed.

In the block 610, if the accrued costs for all local features exceed thethreshold, as set in the reference description, then that symbolicvariant is rejected as a result of recognition.

In the block 612, if the accrued costs for all local features do notexceed the threshold, as set in the reference description, then thatsymbolic variant is accepted as a possible candidate for a result ofrecognition. Eventually, a set of cost function results is formed. Theset of cost function results is based on non-rejected symbolic variants,i.e., reference descriptions. Note that the blocks 602-612 describe aloop over most or all available templates. Therefore, the process 600does not proceed further until the loop is completed and an examinationof most or all available templates is complete.

In a block 614, a set of remaining templates is sorted based on cost,such as from low to high or high to low, such as via a sortingalgorithm, such as an insertion sort, a selection sort, a merge sort, aheap sort, a quick sort, a bubble sort, a shell sort, a comb sort, acounting sort, a bucket sort, a radix sort, or any other sort.

In a block 616, a member of a sorted set is identified, with the memberbeing associated with a minimum cost. For example, a member of a set ofsorted cost function results is identified, wherein the member isassociated with a minimum cost. Note that more than one member can beidentified.

In a block 618, the member is nominated as the symbol. For example, as aresult of a character recognition phase, one or more referencedescriptions or variants with minimum costs are selected to correspondto the symbol. In some embodiments, all remaining reference descriptionsor variants are provided, yet under a condition, such as limiting to anumber of output symbol matches, such as 5 matches, or discarding orignoring those remaining reference descriptions or variants that have acost clearly greater than others. Further, the member(s) with theminimum cost is nominated for character recognition, i.e., one or morereference descriptions or variants with minimum costs are output forcorresponding to the symbol.

In some embodiments, the process 300 can be performed, in whole or inpart, by at least one of a desktop computer, a workstation computer, alaptop computer, a terminal computer, a tablet computer, a mobile phone,an eyewear computer, a vehicle computer, a server computer, acloud-computing system, a mainframe, a supercomputer, or other suitablecomputers. In some embodiments, the vehicle computer is embodied as atleast one of a ground vehicle computer, a marine vehicle computer, anaerial vehicle computer, or a space vehicle computer.

Various embodiments of the present disclosure may be implemented in adata processing system suitable for storing and/or executing programcode that includes at least one processor coupled directly or indirectlyto memory elements through a system bus. The memory elements include,for instance, local memory employed during actual execution of theprogram code, bulk storage, and cache memory which provide temporarystorage of at least some program code in order to reduce the number oftimes code must be retrieved from bulk storage during execution.

Input/Output or I/O devices (including, but not limited to, keyboards,displays, pointing devices, DASD, tape, CDs, DVDs, thumb drives andother memory media, etc.) can be coupled to the system either directlyor through intervening I/O controllers. Network adapters may also becoupled to the system to enable the data processing system to becomecoupled to other data processing systems or remote printers or storagedevices through intervening private or public networks. Modems, cablemodems, and Ethernet cards are just a few of the available types ofnetwork adapters.

The present disclosure may be embodied in a system, a method, and/or acomputer program product. The computer program product may include acomputer readable storage medium (or media) having computer readableprogram instructions thereon for causing a processor to carry outaspects of the present disclosure. The computer readable storage mediumcan be a tangible device that can retain and store instructions for useby an instruction execution device. The computer readable storage mediummay be, for example, but is not limited to, an electronic storagedevice, a magnetic storage device, an optical storage device, anelectromagnetic storage device, a semiconductor storage device, or anysuitable combination of the foregoing. A non-exhaustive list of morespecific examples of the computer readable storage medium includes thefollowing: a portable computer diskette, a hard disk, a random accessmemory (RAM), a read-only memory (ROM), an erasable programmableread-only memory (EPROM or Flash memory), a static random access memory(SRAM), a portable compact disc read-only memory (CD-ROM), a digitalversatile disk (DVD), a memory stick, a floppy disk, a mechanicallyencoded device such as punch-cards or raised structures in a groovehaving instructions recorded thereon, and any suitable combination ofthe foregoing.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present disclosure may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. A code segment ormachine-executable instructions may represent a procedure, a function, asubprogram, a program, a routine, a subroutine, a module, a softwarepackage, a class, or any combination of instructions, data structures,or program statements. A code segment may be coupled to another codesegment or a hardware circuit by passing and/or receiving information,data, arguments, parameters, or memory contents. Information, arguments,parameters, data, etc. may be passed, forwarded, or transmitted via anysuitable means including memory sharing, message passing, token passing,network transmission, among others. The computer readable programinstructions may execute entirely on the user's computer, partly on theuser's computer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer or entirely on the remotecomputer or server. In the latter scenario, the remote computer may beconnected to the user's computer through any type of network, includinga local area network (LAN) or a wide area network (WAN), or theconnection may be made to an external computer (for example, through theInternet using an Internet Service Provider). In some embodiments,electronic circuitry including, for example, programmable logiccircuitry, field-programmable gate arrays (FPGA), or programmable logicarrays (PLA) may execute the computer readable program instructions byutilizing state information of the computer readable programinstructions to personalize the electronic circuitry, in order toperform aspects of the present disclosure.

Aspects of the present disclosure are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of thedisclosure. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions. The various illustrative logicalblocks, modules, circuits, and algorithm steps described in connectionwith the embodiments disclosed herein may be implemented as electronichardware, computer software, or combinations of both. To clearlyillustrate this interchangeability of hardware and software, variousillustrative components, blocks, modules, circuits, and steps have beendescribed above generally in terms of their functionality. Whether suchfunctionality is implemented as hardware or software depends upon theparticular application and design constraints imposed on the overallsystem. Skilled artisans may implement the described functionality invarying ways for each particular application, but such implementationdecisions should not be interpreted as causing a departure from thescope of the present disclosure.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present disclosure. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

Words such as “then,” “next,” etc. are not intended to limit the orderof the steps; these words are simply used to guide the reader throughthe description of the methods. Although process flow diagrams maydescribe the operations as a sequential process, many of the operationscan be performed in parallel or concurrently. In addition, the order ofthe operations may be re-arranged. A process may correspond to a method,a function, a procedure, a subroutine, a subprogram, etc. When a processcorresponds to a function, its termination may correspond to a return ofthe function to the calling function or the main function.

Although preferred embodiments have been depicted and described indetail herein, it will be apparent to those skilled in the relevant artthat various modifications, additions, substitutions and the like can bemade without departing from the spirit of the disclosure, and these are,therefore, considered to be within the scope of the disclosure, asdefined in the following claims.

Features or functionality described with respect to certain exampleembodiments may be combined and sub-combined in and/or with variousother example embodiments. Also, different aspects and/or elements ofexample embodiments, as disclosed herein, may be combined andsub-combined in a similar manner as well. Further, some exampleembodiments, whether individually and/or collectively, may be componentsof a larger system, wherein other procedures may take precedence overand/or otherwise modify their application. Additionally, a number ofsteps may be required before, after, and/or concurrently with exampleembodiments, as disclosed herein. Note that any and/or all methodsand/or processes, at least as disclosed herein, can be at leastpartially performed via at least one entity or actor in any manner.

The terminology used herein can imply direct or indirect, full orpartial, temporary or permanent, action or inaction. For example, whenan element is referred to as being “on,” “connected” or “coupled” toanother element, then the element can be directly on, connected orcoupled to the other element and/or intervening elements can be present,including indirect and/or direct variants. In contrast, when an elementis referred to as being “directly connected” or “directly coupled” toanother element, there are no intervening elements present.

Although the terms first, second, etc. can be used herein to describevarious elements, components, regions, layers and/or sections, theseelements, components, regions, layers and/or sections should notnecessarily be limited by such terms. These terms are used todistinguish one element, component, region, layer or section fromanother element, component, region, layer or section. Thus, a firstelement, component, region, layer, or section discussed below could betermed a second element, component, region, layer, or section withoutdeparting from the teachings of the present disclosure.

Furthermore, relative terms such as “below,” “lower,” “above,” and“upper” can be used herein to describe one element's relationship toanother element as illustrated in the accompanying drawings. Suchrelative terms are intended to encompass different orientations ofillustrated technologies in addition to the orientation depicted in theaccompanying drawings. For example, if a device in the accompanyingdrawings were turned over, then the elements described as being on the“lower” side of other elements would then be oriented on “upper” sidesof the other elements. Similarly, if the device in one of the figureswere turned over, elements described as “below” or “beneath” otherelements would then be oriented “above” the other elements. Therefore,the example terms “below” and “lower” can encompass both an orientationof above and below.

The terminology used herein is for describing particular exampleembodiments and is not intended to be necessarily limiting of thepresent disclosure. As used herein, the singular forms “a,” “an” and“the” are intended to include the plural forms as well, unless thecontext clearly indicates otherwise. The terms “comprises,” “includes”and/or “comprising,” “including” when used in this specification,specify the presence of stated features, integers, steps, operations,elements, and/or components, but do not preclude the presence and/oraddition of one or more other features, integers, steps, operations,elements, components, and/or groups thereof.

As used herein, the term “or” is intended to mean an inclusive “or”rather than an exclusive “or.” That is, unless specified otherwise, orclear from context, “X employs A or B” is intended to mean any of thenatural inclusive permutations. That is, if X employs A; X employs B; orX employs both A and B, then “X employs A or B” is satisfied under anyof the foregoing instances.

Unless otherwise defined, all terms (including technical and scientificterms) used herein have the same meaning as commonly understood by oneof ordinary skill in the art to which this disclosure belongs. Theterms, such as those defined in commonly used dictionaries, should beinterpreted as having a meaning that is consistent with their meaning inthe context of the relevant art and should not be interpreted in anidealized and/or overly formal sense unless expressly so defined herein.

As used herein, the term “about” and/or “substantially” refers to a+/−10% variation from the nominal value/term. Such variation is alwaysincluded in any given.

If any disclosures are incorporated herein by reference and suchdisclosures conflict in part and/or in whole with the presentdisclosure, then to the extent of conflict, and/or broader disclosure,and/or broader definition of terms, the present disclosure controls. Ifsuch disclosures conflict in part and/or in whole with one another, thento the extent of conflict, the later-dated disclosure controls.

What is claimed is:
 1. A method comprising: generating, by a processor, a description of a character symbol from a binarized image, wherein the binarized image depicts an alphanumeric character of a license plate; comparing, by the processor, a template for the character symbol with the description of the character symbol based on a reference description, wherein the template comprises a grid of cells, a set of local features which may be present in the grid of cells, the reference description specifying which member of the set of local features should be present or absent in the grid of cells, and a threshold of an accepted deviation with the description of the character symbol, wherein the reference description comprises a mask table set and a pattern table set, wherein the mask table set specifies cells in which presence or absence of a respective local feature is meaningful for recognition, wherein the pattern table set indicates whether or not a given local feature should be present in a given cell of the character symbol; assigning, by the processor, a penalty value to the description of the character symbol via a cost function when a discrepancy exists based on the comparing; selecting, by the processor, the template as a match candidate for the character symbol when the penalty value is below the threshold; and recognizing, by the processor, the character symbol based on the selecting.
 2. The method of claim 1, wherein a ratio of a number of cells by height and width in the grid of cells substantially corresponds to a ratio of a recognizable font of the character symbol.
 3. The method of claim 1, wherein the grid of cells is a first grid of cells, wherein the generating of the description of the character symbol comprises: segmenting, by the processor, a bounding box into a second grid of cells, wherein the bounding box contains the character symbol, wherein the first grid of cells is equivalent to the second grid of cells, wherein the second grid of cells contains a plurality of pixels, each cell of the second grid of cells contains a set of pixels; determining, by the processor, for each pixel in the set of pixels of each cell of the second grid of cells, a presence or an absence of a local feature from the set of local features; determining, by the processor, for each cell of the second grid of cells, a presence or an absence of a local feature from the set of local features based on an application of a rule to an individual pixel included in that respective cell.
 4. The method of claim 1, wherein the grid of cells is a first grid of cells, wherein the description of the character symbol comprises a second grid of cells equivalent to the first grid of cells, wherein the comparing comprises: for each local feature of the reference description which mandates a presence or an absence of a specified local feature and for each cell in the second grid of cells, verifying, by the processor, the presence or the absence in the description of the image.
 5. The method of claim 1, further comprising: rejecting, by the processor, the template as the match candidate for the character symbol when the penalty value is above the threshold.
 6. A system comprising: a server configured to: generate a description of a character symbol from a binarized image, wherein the binarized image depicts an alphanumeric character of a license plate; compare a template for the character symbol with the description of the character symbol based on a reference description, wherein the template comprises a grid of cells, a set of local features which may be present in the grid of cells, the reference description specifying which member of the set of local features should be present or absent in the grid of cells, and a threshold of an accepted deviation with the description of the character symbol, wherein the reference description comprises a mask table set and a pattern table set, wherein the mask table set specifies cells in which presence or absence of a respective local feature is meaningful for recognition, wherein the pattern table set indicates whether or not a given local feature should be present in a given cell of the character symbol; assign a penalty value to the description of the character symbol via a cost function when a discrepancy exists based on the comparing; select the template as a match candidate for the character symbol when the penalty value is below the threshold; and recognize the character symbol based on the selecting.
 7. The system of claim 6, wherein a ratio of a number of cells by height and width in the grid of cells substantially corresponds to a ratio of a recognizable font of the character symbol.
 8. The system of claim 6, wherein the grid of cells is a first grid of cells, wherein the server is further configured to generate the description of the character symbol via: segmenting a bounding box into a second grid of cells, wherein the bounding box contains the character symbol, wherein the first grid of cells is equivalent to the second grid of cells, wherein the second grid of cells contains a plurality of pixels, each cell of the second grid of cells contains a set of pixels; determining for each pixel in the set of pixels of each cell of the second grid of cells, a presence or an absence of a local feature from the set of local features; determining for each cell of the second grid of cells, a presence or an absence of a local feature from the set of local features based on an application of a rule to an individual pixel included in that respective cell.
 9. The system of claim 6, wherein the grid of cells is a first grid of cells, wherein the description of the character symbol comprises a second grid of cells equivalent to the first grid of cells, wherein the server is further configured to compare the template with the description via: for each local feature of the reference description which mandates a presence or an absence of a specified local feature and for each cell in the second grid of cells, verifying the presence or the absence in the description of the image.
 10. The system of claim 6, wherein the server is further configured to: reject the template as the match candidate for the character symbol when the penalty value is above the threshold.
 11. A method comprising: generating, by a processor, a description of a character symbol from a binarized image, wherein the binarized image depicts an alphanumeric character of a license plate; comparing, by the processor, a template for the character symbol with the description of the character symbol based on a reference description, wherein the template comprises a grid of cells, a set of local features which may be present in the grid of cells, the reference description specifying which member of the set of local features should be present or absent in the grid of cells, and a threshold of an accepted deviation with the description of the character symbol, wherein the reference description comprises a mask table set and a pattern table set, wherein the mask table set specifies cells in which presence or absence of a respective local feature is meaningful for recognition, wherein the pattern table set indicates whether or not a given local feature should be present in a given cell of the character symbol, wherein the grid of cells is a first grid of cells, wherein the description of the character symbol comprises a second grid of cells equivalent to the first grid of cells, wherein the comparing comprises for each local feature of the reference description which mandates a presence or an absence of a specified local feature and for each cell in the second grid of cells, verifying, by the processor, the presence or the absence in the description of the image; assigning, by the processor, a penalty value to the description of the character symbol via a cost function when a discrepancy exists based on the comparing; selecting, by the processor, the template as a match candidate for the character symbol when the penalty value is below the threshold; and recognizing, by the processor, the character symbol based on the selecting.
 12. The method of claim 11, wherein the generating of the description of the character symbol comprises: segmenting, by the processor, a bounding box into a third grid of cells, wherein the bounding box contains the character symbol, wherein the first grid of cells is equivalent to the third grid of cells, wherein the third grid of cells contains a plurality of pixels, each cell of the third grid of cells contains a set of pixels; determining, by the processor, for each pixel in the set of pixels of each cell of the third grid of cells, a presence or an absence of a local feature from the set of local features; determining, by the processor, for each cell of the third grid of cells, a presence or an absence of a local feature from the set of local features based on an application of a rule to an individual pixel included in that respective cell.
 13. The method of claim 12, further comprising: rejecting, by the processor, the template as the match candidate for the character symbol when the penalty value is above the threshold.
 14. The method of claim 13, wherein a ratio of a number of cells by height and width in the grid of cells substantially corresponds to a ratio of a recognizable font of the character symbol. 